Applied Statistics Using SPSS, STATISTICA and MATLAB

Name: Applied Statistics Using SPSS, STATISTICA and MATLAB
Brand: Springer
Price: 85.59 EUR
Availability: OutOfStock

Joaquim P. Marques de Sá(Author)

Springer (Publisher)

Published on 12. June 2003

Book

Mixed media product

XXII, 452 pages

978-3-540-01156-9 (ISBN)

€85.59incl. 7% vat

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Description

Assuming no previous statistics education, this practical reference provides a comprehensive introduction and tutorial on the main statistical analysis topics, demonstrating their solution with the most common software package. Intended for anyone needing to apply statistical analysis to a large variety of science and enigineering problems, the book explains and shows how to use SPSS, MATLAB, STATISTICA and R for analysis such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. It concisely explains key concepts and methods, illustrated by practical examples using real data, and includes a CD-ROM with software tools and data sets used in the examples and exercises. Readers learn which software tools to apply and also gain insights into the comparative capabilities of the primary software packages.

Reviews / Votes

From the reviews:

"Aimed at students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA, this book provides a comprehensive coverage of the main statistical analysis topics . . The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. . The accompanying CD-ROM includes several specific software tools for the topics described in this book . ." (T. Postelnicu, Zentralblatt MATH, Vol. 1028, 2004)

From the reviews of the second edition:

"Readership: Students, professionals and research workers . who are interested in statistical methods and statistical program packages. The book is a . large treatment of many basic statistical methods and procedures. It presents both theoretical issues and a wide variety of applications, examples and exercises. These cover such areas as engineering, medicine, biology, psychology, economy, geology, and astronomy. . After all, I would easily recommend this book for those who are interested in the program packages mentioned in the title." (Kimmo Vehkalahti, International Statistical Review, Vol. 75 (3), 2007)

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Content

1 Introduction.- 2 Presenting and Summarising the Data.- 3 Estimating Data Parameters.- 4 Parametric Tests of Hypotheses.- 5 Non-Parametric Tests of Hypotheses.- 6 Statistical Classification.- 7 Data Regression.- 8 Data Structure Analysis.- 9 Survival Analysis.- 10 Directional Data.- Appendix A - Short Survey on Probability Theory.- A.1 Basic Notions.- A.1.1 Events and Frequencies.- A.1.2 Probability Axioms.- A.2 Conditional Probability and Independence.- A.2.1 Conditional Probability and Intersection Rule.- A.2.2 Independent Events.- A.3 Compound Experiments.- A.4 Bayes' Theorem.- A.5 Random Variables and Distributions.- A.5.1 Definition of Random Variable.- A.5.2 Distribution and Density Functions.- A.5.3 Transformation of a Random Variable.- A.6 Expectation, Variance and Moments.- A.6.1 Definitions and Properties.- A.6.2 Moment-Generating Function.- A.6.3 Chebyshev Theorem.- A.7 The Binomial and Normal Distributions.- A.7.1 The Binomial Distribution.- A.7.2 The Laws of Large Numbers.- A.7.3 The Normal Distribution.- A.8 Multivariate Distributions.- A.8.1 Definitions.- A.8.2 Moments.- A.8.3 Conditional Densities and Independence.- A.8.4 Sums of Random Variables.- A.8.5 Central Limit Theorem.- Appendix B - Distributions.- B.1 Discrete Distributions.- B.1.1 Bernoulli Distribution.- B.1.2 Uniform Distribution.- B.1.3 Geometric Distribution.- B.1.4 Hypergeometric Distribution.- B.1.5 Binomial Distribution.- B.1.6 Multinomial Distribution.- B.1.7 Poisson Distribution.- B.2 Continuous Distributions.- B.2.1 Uniform Distribution.- B.2.2 Normal Distribution.- B.2.3 Exponential Distribution.- B.2.4 Weibull Distribution.- 6.2.5 Gamma Distribution.- B.2.6 Beta Distribution.- B.2.7 Chi-Square Distribution.- B.2.8 Student's t Distribution.- B.2.9 F Distribution.- B.2.10 Von Mises Distributions.- Appendix C - Point Estimation.- C.1 Definitions.- C.2 Estimation of Mean and Variance.- Appendix D - Tables.- D.1 Binomial Distribution.- D.2 Normal Distribution.- D.4 Chi-Square Distribution.- Appendix E - Datasets.- E.1 Breast Tissue.- E.2 Car Sale.- E.3 Cells.- E.4 Clays.- E.5 Cork Stoppers.- E.6 CTG.- E.7 Culture.- E.8 Fatigue.- E.9 FHR.- E.10 FHR-Apgar.- E.11 Firms.- E.12 Flow Rate.- E.13 Foetal Weight.- E.14 Forest Fires.- E.15 Freshmen.- E.16 Heart Valve.- E.17 Infarct.- E.18 Joints.- E.19 Metal Firms.- E.20 Meteo.- E.21 Moulds.- E.22 Neonatal.- E.23 Programming.- E.24 Rocks.- E.25 Signal & Noise.- E.26 Soil Pollution.- E.27 Stars.- E.28 Stock Exchange.- E.29 VCG.- E.30 Wave.- E.31 Weather.- E.32 Wines.- Appendix F - Tools.- F.1 MATLAB Functions.- F.2 Tools EXCEL File.- F.3 SCSIZE Program.- References.

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